codemode

Two MCP tools that replace hundreds. Give an AI agent your OpenAPI spec and a request handler — it discovers and calls your entire API by writing JavaScript in a sandboxed runtime.

Instead of defining individual MCP tools for every API endpoint (list-pods, create-product, get-logs, ...), CodeMode exposes just two tools:

• search — the agent writes JS to filter your OpenAPI spec and discover endpoints
• execute — the agent writes JS to call your API via an injected client

This is the same pattern Cloudflare uses to expose 2,500+ API endpoints through just two MCP tools, reducing context window usage by 99.9%.

Try It

Requires mise for tooling (Node.js, pnpm, Task):

git clone https://github.com/cnap-tech/codemode.git
cd codemode
mise install   # installs Node 24, pnpm 10, Task
task install   # installs dependencies
task example   # runs the Petstore demo

Fetches the real Petstore OpenAPI spec from the web, then runs search + execute against a local Hono mock — no API keys needed.

Install

pnpm add @robinbraemer/codemode

# Install the sandbox runtime:
pnpm add isolated-vm       # V8 isolates

Quick Start

import { CodeMode } from '@robinbraemer/codemode';
import { Hono } from 'hono';

const app = new Hono();
app.get('/v1/clusters', (c) => c.json([{ id: '1', name: 'prod' }]));
app.post('/v1/clusters', async (c) => {
  const body = await c.req.json();
  return c.json({ id: '2', ...body }, 201);
});

const codemode = new CodeMode({
  spec: myOpenAPISpec,              // OpenAPI 3.x spec, or async getter
  request: app.request.bind(app),   // in-process, no network hop
});

// The agent searches the spec to discover endpoints...
const search = await codemode.callTool('search', {
  code: `async () => {
    const results = [];
    for (const [path, methods] of Object.entries(spec.paths)) {
      for (const [method, op] of Object.entries(methods)) {
        if (op.tags?.some(t => t.toLowerCase() === 'clusters')) {
          results.push({ method: method.toUpperCase(), path, summary: op.summary });
        }
      }
    }
    return results;
  }`
});

// ...then executes API calls
const result = await codemode.callTool('execute', {
  code: `async () => {
    const res = await api.request({ method: "GET", path: "/v1/clusters" });
    return res.body;
  }`
});

MCP Server Integration

import { McpServer } from '@modelcontextprotocol/sdk/server/mcp.js';
import { StdioServerTransport } from '@modelcontextprotocol/sdk/server/stdio.js';
import { CodeMode } from '@robinbraemer/codemode';
import { registerTools } from '@robinbraemer/codemode/mcp';

const codemode = new CodeMode({
  spec: () => fetchOpenAPISpec(),
  request: app.request.bind(app),
});

const server = new McpServer({ name: 'my-api', version: '1.0.0' });
registerTools(codemode, server);

const transport = new StdioServerTransport();
await server.connect(transport);

How It Works

AI Agent
  │ writes JavaScript code
  ▼
CodeMode MCP Server
  │
  ├─ search(code) → runs JS with preprocessed OpenAPI spec
  │   → all $refs resolved inline, only essential fields kept
  │   → agent discovers endpoints, schemas, parameters
  │
  └─ execute(code) → runs JS with injected request client
      → api.request() calls your handler in-process
      → no network hop, auth handled automatically

All code runs in an isolated V8 sandbox. The sandbox has zero I/O by default — no require, no process, no fetch, no filesystem. The only way to interact with the outside world is through the injected globals (spec for search, {namespace}.request() for execute).

Each tool call gets a fresh sandbox with no state carried over between calls.

API

new CodeMode(options)

SandboxOptions

Methods

codemode.tools(): ToolDefinition[]

Returns MCP-compatible tool definitions for search and execute.

codemode.callTool(name, { code }): Promise<ToolCallResult>

Route a tool call. Returns { content: [{ type: "text", text }], isError? }.

codemode.search(code): Promise<ToolCallResult>

Run search code directly (shorthand for callTool('search', { code })).

codemode.execute(code): Promise<ToolCallResult>

Run execute code directly (shorthand for callTool('execute', { code })).

codemode.setToolNames(search, execute): this

Override default tool names. Useful when running multiple CodeMode instances.

codemode.dispose(): void

Clean up sandbox resources.

Sandbox API

Inside search

The spec global is the preprocessed OpenAPI spec with all $ref pointers resolved inline:

// Find endpoints by tag
async () => {
  const results = [];
  for (const [path, methods] of Object.entries(spec.paths)) {
    for (const [method, op] of Object.entries(methods)) {
      if (op.tags?.some(t => t.toLowerCase() === 'clusters')) {
        results.push({ method: method.toUpperCase(), path, summary: op.summary });
      }
    }
  }
  return results;
}

// Get endpoint with requestBody schema (refs are already resolved)
async () => {
  const op = spec.paths['/v1/products']?.post;
  return { summary: op?.summary, requestBody: op?.requestBody };
}

// Spec metadata
async () => ({
  title: spec.info.title,
  version: spec.info.version,
  endpoints: Object.keys(spec.paths).length,
})

Inside execute

The {namespace}.request() function makes API calls through the host handler:

// GET with query params
async () => {
  const res = await api.request({
    method: "GET",
    path: "/v1/clusters",
    query: { limit: 10 },
  });
  return res.body;
}

// POST with body
async () => {
  const res = await api.request({
    method: "POST",
    path: "/v1/products",
    body: { name: "Redis", chart: "bitnami/redis" },
  });
  return { status: res.status, body: res.body };
}

// Chain calls
async () => {
  const list = await api.request({ method: "GET", path: "/v1/clusters" });
  const details = await Promise.all(
    list.body.map(c =>
      api.request({ method: "GET", path: `/v1/clusters/${c.id}` })
    )
  );
  return details.map(d => d.body);
}

Request options:

Response: { status: number, headers: Record<string, string>, body: unknown }

Spec Preprocessing

CodeMode automatically preprocesses your OpenAPI spec before passing it to the search sandbox:

• $ref resolution — all $ref pointers are resolved inline (circular refs become { $circular: ref })
• Field extraction — only essential fields kept per operation: summary, description, tags, operationId, parameters, requestBody, responses
• Metadata preserved — info, servers, and components.schemas are kept alongside processed paths

You can also use the preprocessing utilities directly:

import { resolveRefs, processSpec, extractTags } from '@robinbraemer/codemode';

const processed = processSpec(rawSpec);
const tags = extractTags(rawSpec);

Executors

CodeMode uses isolated-vm (V8 isolates) for sandboxed execution. You can pass a custom instance:

import { CodeMode, IsolatedVMExecutor } from '@robinbraemer/codemode';

const codemode = new CodeMode({
  spec,
  request: handler,
  executor: new IsolatedVMExecutor({
    memoryMB: 128,
    timeoutMs: 60_000,   // CPU time limit
    wallTimeMs: 120_000, // total elapsed time limit
  }),
});

Custom Executor

Implement the Executor interface to use your own sandbox:

import { CodeMode, type Executor, type ExecuteResult } from '@robinbraemer/codemode';

class MyExecutor implements Executor {
  async execute(code: string, globals: Record<string, unknown>): Promise<ExecuteResult> {
    // `code` is an async arrow function as a string: "async () => { ... }"
    // `globals` contains named values to inject:
    //   - plain data (objects, arrays, primitives) → read-only values
    //   - functions → callable host functions
    //   - objects with function values → namespace with callable methods
    return { result: ..., logs: [] };
  }

  dispose() { /* clean up */ }
}

const codemode = new CodeMode({
  spec,
  request: handler,
  executor: new MyExecutor(),
});

Token Efficiency

License

MIT